fitting mixed effects logistic regression with weights

Dear Ben,

Thank you for your prompt response.  Does MCMCglmm provide the usual
REML/RSPL estimates or Bayesian estimates for the fixed effects? I
mean are the coefficient and SE estimates REML/RSPL or Bayesian? I
want to be sure what I am getting.

Mulugeta ________________________________________ From:
r-sig-mixed-models-bounces at r-project.org
[r-sig-mixed-models-bounces at r-project.org] On Behalf Of Ben Bolker
[bbolker at gmail.com] Sent: Friday, June 10, 2011 4:33 PM To:
r-sig-mixed-models at r-project.org Subject: Re: [R-sig-ME] fitting
mixed effects logistic regression with  weights

On 06/10/2011 04:24 PM, Gebregziabher, Mulugeta wrote:

Dear all,

I have been trying to fit a logistic regression model with random 
intercept for survey sampled data using the lmer in the lme4
package. I also want to get HPD intervals. I tried family=binomial
as well as family=quasibinomial. I am encountering the following
errors. "Eror in .local(object, n, verbose, ...) : Update not yet
written" and "Error in HPD interval(mcmcsamp(fit, 1000)) :   error
in evaluating the argument 'object' in selecting a method for
function 'HPDinterval'.

As the error message suggests (obliquely!), mcmcsamp() does not yet 
work for GLMMs (i.e. [g]lmer with 'family' specified).  Furthermore, 
quasi-likelihood fitting no longer works with the latest releases of 
lme4 (because the author decided that he didn't really understand
what it was doing, hence safer to omit it).

Have you considered MCMCglmm, or parametric bootstrapping 
(help("simulate-mer")) ?


See more below:

Does anyone know how to go around this problem? Thanks.

library(lme4)

Loading required package: Matrix Loading required package: lattice 
Attaching package: 'Matrix' The following object(s) are masked
from 'package:base': det Attaching package: 'lme4' The following
object(s) are masked from 'package:stats': AIC

attach(cohort)

f  <- a1cge8 ~  (1|id)   +  time  +  nhb  + hispanic  + other  + 
male  + mstat  +svcpct   +urban   +  comor1   +comor2  + comor3


est        <- round(slot(summary(fit), "coefs")[,1], digits=2) t 
<- slot(summary(fit), "coefs")[,3] df      <- c(1, 1, 3, 3, 3,
1, 1, 1, 1, 3, 3, 3) p.value    <- ifelse(t<0, round(pt(t,
df=df), digits=3), round(1-pt(t, df), digits=3) ) se         <- 
round(slot(summary(fit), "coefs")[,2], digits=4) ci         <- 
HPDinterval(mcmcsamp(fit, 1000))

Error in .local(object, n, verbose, ...) : Update not yet written 
Error in HPDinterval(mcmcsamp(fit, 1000)) : error in evaluating
the argument 'object' in selecting a method for function
'HPDinterval'

lower <- round(ci$fixef[,1], digits=2)

Error: object 'ci' not found

upper <- round(ci$fixef[,2], digits=2)

Error: object 'ci' not found